On coupling analysis of protein networks of helicobacter pylori - human host and prediction technique of gastropathy clinical outcomes

HP (helicobacter pylori) is a main cause of human chronic gastroduodenal disease including gastric cancer. Study protein interaction of the pathogen and its host will contribute to understanding of the pathogenesis. System (network) biology is introduced into the project to establish firstly a coupled subnet (CSN) from the interaction of a HP protein network (PN) and its host PN. Next, several characteristic parameters are exacted from a CSN to measure the relationship of the CSN and a gastric disease. Then, an artificial neural network (ANN) and a support vector machine (SVM) are used to mine parameters of the CSN to find features of the disease, and a model to predict clinical outcomes of the HP infection is formed and tested lastly. The study will play an active role in gastropathy prevention and treatment.